Mechanical Systems and Signal Processing Submission Guide

Source: ScienceDirect MSSP journal page and author guide, accessed May 2026.

Source: MSSP author guidelines.

Use this page when deciding:

• whether the signal-processing contribution is substantive

• whether mechanical-systems validation is rigorous

• whether benchmarking is comprehensive

• a clear signal-processing advance

• mechanical-systems validation

• benchmarking against state-of-the-art

• comprehensive performance metrics

• a cover letter establishing the contribution

• Incremental signal-processing improvements without novel principle.

• Missing benchmarking against state-of-the-art methods.

• Weak mechanical-systems validation.

• General signal processing without mechanical focus.

MSSP is a flagship signal-processing journal for mechanical systems.

Mechanical-systems standard: the journal differentiates from IEEE Transactions on Signal Processing (broader) and Journal of Sound and Vibration (vibration-specific) by demanding signal-processing advances with mechanical-systems applications.

Validation expectation: editors expect demonstrated application to mechanical systems.

The desk screen: MSSP's public guide makes the initial suitability screen decisive because the manuscript must show original engineering contribution, method-family positioning, and verification in the results rather than only a performance gain.

The strongest MSSP cover letters establish:

• the signal-processing contribution

• the mechanical-systems validation

• the benchmarking approach

• the central finding

Mechanical Systems and Signal Processing (MSSP) submissions go through Elsevier Editorial Manager at Editorial Manager submission portal. Initial setup requires an Elsevier account; ORCID is recommended for the corresponding author. The platform accepts Research Papers and Reviews on signal processing in mechanical, aerospace, and civil engineering contexts.

For some Review-type and ML-focused submissions, the journal advises prospective authors to send a proposal (article title, authors with titles and affiliations, article summary, and table of contents) to the Editor-in-Chief for prior approval before full submission. Full guide at the MSSP author page.

Mechanical Systems and Signal Processing requires these at first submission:

• Cover letter explicitly establishing the demonstrable original contribution to engineering knowledge and the significance over established methods

• Declaration of competing interests for all authors

• Generative AI usage declaration covering manuscript preparation and figure generation

• Data availability statement with repository links for vibration data, signal records, or experimental measurements

• Code availability statement for any signal-processing algorithms or computational methods

• CRediT author contributions statement

• For ML or soft-computing-focused submissions: prior proposal approval from the Editor-in-Chief referenced in the cover letter (MSSP rejects many ML submissions without review when they do not conform to journal standards)

• Editable source files (Word (.docx) or LaTeX (.tex)); PDFs are not acceptable

• Four or more suggested reviewers with no recent collaboration history

For MSSP submissions, the most common artifact-related desk-screen problem is a machine-learning or signal-processing manuscript whose cover letter, abstract, and methods table do not explain the mechanical-system contribution. MSSP's guide asks authors to spell out the problem, the principle of the solution approach, the innovative contribution, and the verification or demonstration. A package that reports a classifier, denoiser, or prognostic model without an engineering-dynamics reason for the method looks like a generic signal-processing submission, even when the test accuracy is high.

For Mechanical Systems and Signal Processing submissions, the editorial timeline runs through four phases. The editorial-stage filter weights theoretical-plus-experimental contributions heavily, especially where the manuscript connects the signal-processing method to mechanical, aerospace, or civil engineering systems.

Day 0 to 5: Editorial Manager intake and editor assignment

Elsevier intake handles format compliance plus the AI-declaration and source-file checks. The handling Editor assignment lands within 5 days; MSSP papers route to subject editors matching the engineering subfield (machine health monitoring, rotor dynamics, structural health monitoring, nonlinear vibration, control of vibration and noise, acoustics). The most common Day 0-5 hold-up: ML-focused submissions without prior Editor-in-Chief approval reference.

Day 5 to 21: Editor scope and theoretical-plus-experimental screen

MSSP's editor filter prioritizes contributions with demonstrable original signal-processing methodology validated against mechanical-systems experimental data. The most common Day 5 to 21 desk-screen problem in our review work: machine learning or soft-computing papers without mechanical-systems experimental validation, and theory-only papers without a practical engineering-dynamics demonstration.

Week 3 to 10: Peer review

Standard 2-3 reviewers, 4-8 week first decision target. Reviewer mix typically includes one signal-processing methodologist plus one mechanical-systems experimental specialist. Submissions missing experimental validation against benchmark datasets or comparison against established signal-processing methods extend reviewer dialogue by 3-5 weeks.

Week 10 to 22: Decision, revision, and production

Major revision is the standard first decision at MSSP. Revision rounds typically settle at 2 (rarely 3 for accepted papers). Total submission-to-acceptance: 5-8 months for accepted papers. Hybrid open-access option available with APC at acceptance.

• Is MSSP a good journal?

Before upload, run your manuscript through an MSSP signal-processing readiness check.

Across mechanical-engineering manuscripts targeting Mechanical Systems and Signal Processing, three named patterns consistently decide whether the paper looks like an MSSP manuscript or a generic signal-processing paper with machinery examples added late.

Algorithmic gain without an engineering-dynamics problem

Across mechanical-dynamics manuscripts targeting Mechanical Systems and Signal Processing, this is the most frequent MSSP failure mode: the abstract leads with a new classifier, denoising architecture, feature extractor, or prognostic model, but the paper does not explain the mechanical-system problem that made the method necessary.

The official MSSP guide asks for a precise problem statement, a digested state-of-the-art review grouped by method family, the principle of the solution approach, and verification that the study goal has been achieved. A manuscript that says "our model improves fault classification by 2.1%" without showing which vibration, rotor-dynamics, structural-health-monitoring, or machining limitation is solved does not pass that bar.

The repair is manuscript-level, not cosmetic. The introduction should name the engineering-dynamics failure case, the abstract should state the mechanical-system consequence, the methods should explain why the signal representation fits that system, the figures should show diagnostic value rather than only confusion matrices, and the cover letter should identify why the work belongs in MSSP instead of IEEE Transactions on Signal Processing, Mechanical Systems and Signal Processing's broader Elsevier siblings, Journal of Sound and Vibration, IEEE Transactions on Industrial Electronics, or Structural Health Monitoring.

Check whether your Mechanical Systems and Signal Processing manuscript frames a real engineering-dynamics problem →

Benchmark table that compares algorithms but not mechanical evidence

Across signal-processing manuscripts targeting MSSP, we often see benchmarking tables that look mathematically complete while still failing the journal fit test. The table compares accuracy, F1 score, RMSE, or computation time against CNN, LSTM, transformer, EMD, wavelet, Kalman, or sparse-representation baselines, but it does not compare the evidence that matters to the mechanical system: operating regime, sensor placement, fault severity, load variation, noise profile, transfer across machines, and whether the dataset represents a real engineering decision.

MSSP's guide explicitly asks for a concise, critical, authoritative state-of-the-art review, not a chronological list of papers.

The stronger MSSP package uses the benchmarking table as an editorial argument. The methods section names which baseline family is being challenged, the results figure shows where the proposed approach fails as well as where it wins, the supplementary material includes enough data and code context for readers to understand the comparison, and the discussion ties improvements to mechanical interpretation.

If that evidence is absent, a paper may be better routed to Measurement, IEEE Sensors Journal, IEEE Transactions on Instrumentation and Measurement, Journal of Sound and Vibration, or a specialist condition-monitoring venue.

Check whether your MSSP benchmarking table supports the journal fit →

Validation package that proves a dataset but not a system

Across MSSP-targeted manuscripts, the most costly validation gap is mistaking dataset performance for mechanical-system validation. A paper may include a public bearing dataset, a laboratory rig, or a finite-element simulation and still leave editors unsure whether the method generalizes to the engineering context MSSP covers.

The manuscript components that need alignment are concrete: the abstract should identify the mechanical decision supported by the method, the methods should define operating conditions and assumptions, the figures should connect signal features to physical behavior, the supplementary files should document data provenance, and the limitations section should say where the method is not ready.

This matters because MSSP sits between pure signal-processing venues and mechanical-dynamics venues. If the contribution is mostly algorithmic, IEEE Transactions on Signal Processing may be cleaner. If the contribution is mostly vibration interpretation, Journal of Sound and Vibration may be cleaner. If the contribution is industrial control or electronics implementation, IEEE Transactions on Industrial Electronics may be cleaner. MSSP is strongest when the algorithm and the mechanical-system interpretation are inseparable.

Check whether your Mechanical Systems and Signal Processing validation package is submission-ready →

The review tells you whether your paper passes the mechanical-system contribution, benchmarking, and validation checks before upload. Manusights checks do not train on your manuscript, and paid reviews include a 60-day money-back guarantee.

How do I submit to Mechanical Systems and Signal Processing?

Submit through Elsevier Editorial Manager. The journal accepts Standard Research Articles, Long Research Articles, Short Communications, Discussions, and invitation-only Reviews or Tutorials. The cover letter should establish the signal-processing contribution and mechanical-systems relevance.

What is MSSP's JIF and acceptance rate?

ScienceDirect displayed an 8.9 JIF and 18.0 CiteScore when this page was reviewed on May 26, 2026. Elsevier does not publicly disclose a dependable acceptance or desk-rejection rate for MSSP.

What does Mechanical Systems and Signal Processing publish?

Original research on signal processing applied to mechanical systems: vibration analysis, condition monitoring, fault diagnosis, structural health monitoring, machine learning for mechanical systems, and emerging signal-processing methods.

Why does MSSP desk-reject most submissions?

Most reasons: incremental signal-processing improvements without novel principle, missing benchmarking against state-of-the-art methods, weak mechanical-systems validation, or scope mismatch (general signal processing without mechanical focus).

In pre-submission diagnostic work for top mechanical-systems signal-processing journals, we check four signals that distinguish strong submissions from weak ones: whether the signal-processing advance is substantive, whether mechanical-systems validation is demonstrated, whether benchmarking against state-of-the-art method families is explicit, and whether performance metrics are tied to a real engineering decision.

For Mechanical Systems and Signal Processing-targeted manuscripts, the single most consistent feedback class we deliver in pre-submission diagnostics for MSSP is the incremental-versus-substantive distinction. MSSP editors expect substantive signal-processing advances combined with mechanical-systems validation. Submissions framed as "we modified algorithm X to achieve Y improvement" routinely invite the question "where is the engineering advance?" We coach authors to lead with the substantive contribution.

Papers framed as "we developed a new signal-processing framework that addresses fault-diagnosis challenge X by exploiting mechanical-system property Y, validated on real machinery data Z" receive better editorial traction.

For Mechanical Systems and Signal Processing-targeted manuscripts, beyond the rubric checks, three pre-submission diagnostic patterns recur most often in the manuscripts we review for MSSP. First, manuscripts where the abstract reports algorithm performance without articulating the substantive contribution are flagged for incremental framing. Second, manuscripts where benchmarking uses literature values without specific comparisons are flagged for benchmarking gaps. Third, manuscripts that lack engagement with MSSP's recent issues are at risk of being told the contribution does not fit the publication conversation.

For Mechanical Systems and Signal Processing-targeted manuscripts, the strongest manuscripts we coach distinguish themselves on three operational behaviors. First, they keep the cover letter focused on the engineering contribution. Second, they include a one-sentence elevator pitch that connects the method to the mechanical system. Third, they identify the specific recent MSSP articles that this manuscript builds on.